Sandeep Reddy

Artificial Intelligence (AI) presents unprecedented opportunities to transform healthcare worldwide, from improving diagnostic accuracy to expanding access in underserved regions. Despite this potential and growing investment, a significant gap persists between AI’s theoretical promise and its realised benefits in healthcare settings. This article examines the complex barriers impeding AI benefits realization in global health contexts, including ethical uncertainties, data infrastructure limitations, evidence quality concerns, and regulatory ambiguities. We analyze current initiatives addressing these challenges and highlight how technological solutions alone cannot resolve fundamental healthcare inequities. Drawing on the interdisciplinary perspectives and insights presented at the Global Health in the Age of AI Symposium hosted by the Cini Foundation and Yale Digital Ethics Center, we propose five core infrastructure requirements necessary for ethical AI implementation: robust data exchange; epistemic certainty with staff autonomy; actively protected healthcare values; validated outcomes with meaningful accountability; and environmental sustainability. These requirements form the foundation for a systems approach that balances technological advancement with ethical imperatives, contextual adaptability, and global equity considerations. We conclude that the successful integration of AI into healthcare demands coordinated action across sectors and borders, with careful attention to avoiding technological colonialism and ensuring AI serves as a force for health equity rather than widening existing disparities.